本文選題：面本體 + 情境本體　； 參考：《西南大學》2013年碩士論文

【摘要】：人們在傳統(tǒng)搜索引擎上所用到的關(guān)鍵字搜索技術(shù)發(fā)展成熟,是當今最流行的搜索方式。但是用戶輸入關(guān)鍵字,搜索自己想要的東西,想表達的意思僅僅用幾個關(guān)鍵詞并不能完全表達清楚,而計算機卻只能根據(jù)關(guān)鍵詞作全文匹配,常常不能達到用戶想要的效果。比如,“椅子”這個詞,它本身的屬性包括了椅子的材質(zhì),形狀,設(shè)計工藝,制作廠家,制作時間,地點等等,這一系列潛在的屬性構(gòu)成了一個復(fù)雜的基于語義的關(guān)聯(lián)網(wǎng)。單純的關(guān)鍵詞匹配已經(jīng)不能適應(yīng)人們對搜索更精細化,人性化的要求。下一代網(wǎng)絡(luò)WEB3.0”語義網(wǎng)”在搜索方面的研究側(cè)重于具有語義分析能力的搜索引擎,要求搜索引擎能夠理解人類的自然語言,并且具有一定的推理和判斷能力。 本文提出了一種基于面本體的情境搜索模型(Context Search Based on Faceted Ontology, CSFO), CSFO模型構(gòu)建面本體FO來表示信息搜索領(lǐng)域的各個屬性面,構(gòu)建情境本體CO來創(chuàng)造用戶搜索的當前情境,CSFO模型的主要思想根據(jù)情境本體CO對用戶輸入的關(guān)鍵字進行語義擴展,生成相應(yīng)的搜索本體SO,通過面本體FO標注獨立數(shù)據(jù)源的異構(gòu)文檔,最后利用相關(guān)的本體匹配算法進行搜索本體與面本體的本體匹配,從面本體中匹配出與當前搜索本體最相似的結(jié)果本體RO,實現(xiàn)情境搜索。CSFO模型旨在為用戶提供更符合用戶當前情境的搜索結(jié)果。本文的研究工作主要包括以下五個方面： 第一,本文將本體技術(shù)整合到信息檢索中,構(gòu)建多個不同的本體數(shù)據(jù)模型表示不同的信息。本文用到的本體數(shù)據(jù)模型包括：情境本體CO,搜索本體SO,面本體FO,結(jié)果本體RO。CO用來表示用戶的情境信息,SO來表示用戶當次的查詢信息,FO來表示被搜索的相關(guān)領(lǐng)域信息,RO用來表示當次的查詢結(jié)果。 第二,本文用搜索本體模型SO代替關(guān)鍵詞進行搜索查詢,將用戶情境信息引入搜索系統(tǒng)。本文利用情境本體模型中的概念詞匯,對用戶在客戶端輸入的關(guān)鍵詞進行語義擴展,規(guī)范用戶自然語言的查詢輸入,提取有檢索意義的概念詞組通過基于情境本體的語義擴展算法SECO生成完成當次搜索的搜索本體模型。用搜索本體代替關(guān)鍵詞進行信息匹配,擴大了用戶情境信息表示的完整度。 第三,本文從不同的獨立數(shù)據(jù)源構(gòu)建面本體FO,規(guī)范搜索信息的表示形式。本文通過下面四個步驟：a.產(chǎn)品系列分類；b.實體擴展；c.生成面單元FU及概念映射；d..面建模；來構(gòu)建一個完整的特定領(lǐng)域的面本體。每個面本體從實體(Entity),性質(zhì)(Property),活動(Action),修正(Modifier)這四個面進行概念分層。本文將被搜索的信息用面本體進行表示,不僅能規(guī)范各個獨立數(shù)據(jù)源的信息,而且能通過面本體擴展各實體,概念及其屬性之間的相關(guān)關(guān)系,豐富情境搜索結(jié)果的內(nèi)容,提高搜索結(jié)果與用戶情境的相關(guān)性。 第四,本文通過搜索本體SO與面本體FO的本體匹配從用戶角度,返回查詢信息,實現(xiàn)情境搜索。本文用到兩種本體匹配的方法進行搜索本體與面本體的本體匹配,其中一種是基于圖的情境搜索算法CRG,該算法借鑒了相似度洪泛算法的思想；另一種是不一致本體推理算法CRIO,是將面本體,情境本體,搜索本體,結(jié)果本體全部抽象成不一致本體,通過不一致本體的推理,從面本體中匹配出與之相似的搜索本體。無論是哪一種方法,最終目的都是在面本體中匹配出與搜索本體最相似的面本體的子本體,然后通過相關(guān)函數(shù)將子本體轉(zhuǎn)換成由標題,日期,鏈接,內(nèi)容這幾個關(guān)鍵字段組成的數(shù)據(jù)信息,形成搜索結(jié)果,返回給用戶實現(xiàn)情境搜索。 第五,實驗分析與評價。為驗證CSFO模型的可行性和有效性,通過仿真實驗對該方法進行了小數(shù)據(jù)集的模擬與實現(xiàn),同時,通過即有的平臺數(shù)據(jù)集進行對比分析,實驗結(jié)果表明,本文提出的方法應(yīng)用于搜索引擎,與傳統(tǒng)的信息搜索比較,具有更好的查全率與查準率。 本文的研究對語義搜索具有一定的促進作用,對推進語義搜索的應(yīng)用研究從理論層面過渡到工業(yè)實現(xiàn)層面也有積極的意義。
[Abstract]:The keyword search technology used by people in the traditional search engine is mature and is the most popular search method in the present day . However , the user inputs the keyword , searches for what you want , and the computer can only use several keywords to fully express clearly , but the computer can only do the full - text match according to the keyword , and the computer can not meet the requirements of the user . For example , the research of the next generation network WEIB3.0 " Semantic Web " focuses on the search engine with semantic analysis capability , which requires the search engine to understand the natural language of the human beings , and has certain reasoning and judgment ability .

A kind of context search based on Faceted Ontology ( CSFO ) is presented in this paper . The main idea of CSFO is to create user ' s current situation . The main idea of CSFO model is to create user ' s current situation . The main idea of CSFO model is to make semantic extension of key words input by user based on context ontology CO .

Firstly , the ontology technology is integrated into the information retrieval to construct a plurality of different ontology data models to represent different information . The ontology data model used in this paper includes : context ontology CO , search ontology SO , face ontology FO , result ontology RO . CO is used to represent user context information , SO to represent user context information , FO to represent the relevant field information searched , and RO is used to represent the results of the query .

secondly , the search query is carried out by using the search ontology model SO in place of the keyword , and the user context information is introduced into the search system .

Third , this paper constructs surface ontology FO from different independent data sources , canonical search information representation form . This paper uses the following four steps : a . product family classification ;
b . Entity extension ;
c . generating surface unit FU and concept mapping ;
d. Surface modeling ;
In this paper , the information of each independent data source can be regulated , and the relationship between each entity , concept and its attributes can be extended through the surface ontology , and the content of the results of the situation search can be enriched , and the relevance of the search result and the user context can be improved .

Fourthly , this paper uses two kinds of ontology matching methods to match the ontology to the ontology , one of which is the context search algorithm CRG based on the graph , which uses the idea of similarity flood algorithm .
The invention relates to an inconsistent ontology reasoning algorithm CRIO , which is characterized in that a face body , a situational ontology and a searching body are all abstracted into inconsistent bodies ;

Fifth , experimental analysis and evaluation . In order to verify the feasibility and effectiveness of CSFO model , the simulation and realization of this method are carried out by simulation experiment .

The research of this paper has a certain promotion effect on the semantic search , and the application research on the promotion of the semantic search has a positive meaning from the theoretical level to the industrial realization level .
【學位授予單位】：西南大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：TP391.1

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本文編號：1951480